The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessing stage is accomplished by removing some artifacts in order to ensure high identification rates. The extracted features are collected as a feature vector; then they are used to distinguish different individuals. In the matching stage, the nearest neighbor classifier is used to make recognition decisions. The results for identification of the proposed system indicate high identification performance reach to 100%, while the verification test results indicate error rate 99.88% using FVC2004 databases.
Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi
... Show MoreThis paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n
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16S rRNA gene sequence examination is an effective instrument for characterization of new pathogens in clinical specimens. Akey component of colonization, biofilm formation, and protection of the pragmatic human pathogen Pseudomonasaeruginosais the biosynthesis of the exopolysaccharide Psl.Extracellular polysaccharides,biofilm, are secreted by microorganisms into the neighboring environment and are significant for surface attachment and keeping structural safety within biofilms.Biofilm production is an important technique for the survival of P. aeruginosa,and its association with antimicrobial resistance represents a defy for patient therapeutics. The aim of the current research is to assess the antibiotic resistance manner and distribution
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The two-frequency shell model approach is used to calculate the
ground state matter density distribution and the corresponding root
mean square radii of the two-proton17Ne halo nucleus with the
assumption that the model space of 15O core nucleus differ from the
model space of extra two loosely bound valence protons. Two
different size parameters bcore and bhalo of the single particle wave
functions of the harmonic oscillator potential are used. The
calculations are carried out for different configurations of the outer
halo protons in 17Ne nucleus and the structure of this halo nucleus
shows that the dominant configuration when the two halo protons in
the 1d5/2 orbi
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Radial density distribution function of one particle D(r1) was calculated for main orbital of carbon atom and carbon like ions (N+ and B- ) by using the Partitioning technique .The results presented for K and L shells for the Carbon atom and negative ion of Boron and positive ion for nitrogen ion . We observed that as atomic number increases the probability of existence of electrons near the nucleus increases and the maximum of the location r1 decreases. In this research the Hartree-fock wavefunctions have been computed using Mathcad computer software .
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The calculation. of the nuclear. charge. density. distributions. ρ(r) and root. mean. square. radius.( RMS ) by elastic. electron. scattering. of medium. mass. nuclei. such. as (90Zr, 92Mo) based. on the model. of the modified. shell. and the use of the probability. of occupation. on the surface. orbits. of level 2p, 2s eroding. shells. and 1g gaining. shells. The occupation probabilities of these states differ noticeably from the predictions of the SSM. We have found. an improvement. in the determination. of ground. charge. density. and this improvement. allow. more precise. identification. of (CDD) between. (92Mo- 90Zr) to illustrate the influence of the extra
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Yersinia enterocolitica has ranked a third among the pathogens that most frequently cause gastrointestinal disorders transmitted to humans through food materials, especially contaminated meats. The meat infected with Yersinia enterocolitica had no change in apparent texture or smell. The aim of this research is to survey the frequency of Y. enterocolitica in ovine meat, compare their ratio of infection between the season, To carry out this study (125) samples of local ovine meat were collected by random sampling from the middle region of Iraq. The samples were divided into two groups steak and mince, then many microbiological tests (culture, & staining, biochemical Tests Api 20E, Vitik 2 and species-specific PCR amplicon for 16S RNA gene) w
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